Hand signals recognition using Convolutional Neural Network implemented in TensorFlow
This repository contains code that I use to build a machine learning model for hand signals recognition system.
The training data is not included. You can create your own training data using webcam via Chrome. I use the following HTML & JS script to collect the training data.
python train.py training-data/
It expect all images inside training-data directory are named using this
format: label_id-* where label_id is natural number and 0 < label_id.
2017-08-15 14:17:17.996850: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996882: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996892: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996900: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996909: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996917: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996925: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:17.996933: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2017-08-15 14:17:18.916319: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\framework\op_kernel.cc:1158] Not found: FindFirstFile failed for: traning-data : The system cannot find the path specified.
2017-08-15 14:17:18.916685: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\35\tensorflow\core\framework\op_kernel.cc:1158] Not found: FindFirstFile failed for: traning-data : The system cannot find the path specified.
Hi,I am wangbing! A student from China! I have a question about your dataset,could you share your data with us?Thanks!
Mas, setelah menjalankan training, bagaimana menjalankan prediksinya? Terima kasih
hi, could you tell me your tensorflow_version? and is it GPU or CPU
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